4 citations · 12 across the 3 of their papers we have counts for
3 papers
Slimmable Encoders for Flexible Split DNNs in Bandwidth and Resource Constrained IoT Systems
Juliano S. Assine, J. C. S. Santos Filho, Eduardo Valle +1
The execution of large deep neural networks (DNN) at mobile edge devices requires considerable consumption of critical resources, such as energy, while imposing demands on hardware…
Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computation
Juliano S. Assine, J. C. S. Santos Filho, Eduardo Valle
In the past few years, mobile deep-learning deployment progressed by leaps and bounds, but solutions still struggle to accommodate its severe and fluctuating operational restrictio…
Compressing Representations for Embedded Deep Learning
Juliano S. Assine, Alan Godoy, Eduardo Valle
Despite recent advances in architectures for mobile devices, deep learning computational requirements remains prohibitive for most embedded devices. To address that issue, we envis…